As machine learning intern, you will be designing and building systems that help Docsumo process visual data. Photographs or scan of documents all rich with information if only we could teach a computer to interpret them.
You'll work in our Machine Intelligence team, a close-knit group of scientists and engineers who incubate new capabilities from whiteboard sketches all the way to finished apps. We take a product-centric approach to research & development, working closely with our customers to identify opportunities and putting as much care into product design as raw capability.
Requirements
- Course work / online degrees in machine learning, text processing, data science, information retrieval, deep learning, natural language processing, text mining, regression, classification, etc.
- Must be enrolled in a full-time degree in Computer Science or similar (Statistics/Mathematics)
- Team player who can take responsibility for anything from fixing the office internet to making a sales pitch to CEO of a company. We believe in the ideology that “Buck stops with me”.
- Hands-on experience applying advanced statistical learning techniques to different types of data.
- Working with Python: Numpy, Scikit-learn, Matplotlib, Pandas
- Working with OpenCV, TensorFlow and Keras
- Ability to understand the business problem, identify the key challenges, formalize the problem algorithmically, and prototype solutions.
- Consistent track record of documenting, synthesizing, and communicating results.
- Ability to design, build and work with RESTful Web Services in JSON and XML formats. (Django and/or Flask preferred)
- Familiarity with Version Control tools such as Git
- Agile principles and processes including (but not limited to) standup meetings, sprints and retrospectives
- Theoretical and practical knowledge of SQL / NoSQL databases with hands-on experience in at least one database system
- Must be self-motivated, flexible, collaborative, with an eagerness to learn
This job is already closed and no longer accepting applicants, sorry.